Should we use a pre-trained model or a blank model for custom entity training of NER in spacy?
The reason you would load a pre-existing model is that it offers something of value to your task (e.g. named entity recognition for food) and the cost of training it from scratch is not worth it.  For example, to train GPT-3 from scratch would cost several million dollars.  Typically someone will use a model like BERT and fine tune it.  This is called transfer learning.  With spaCy you will typically use en_core_web_sm which was trained on the OntoNotes corpus and includes named entities.  Making a custom food NER using en_core_web_sm should be more accurate than making one from scratch. You should be able to build a good model with and without transfer learning fairly quickly if you have a GPU.